Data Standardisation

October 3, 2016

A large global banking client was seeking to transform the way that data was used within its Investment Bank. The aim was to manage the data more efficiently, consistently and transparently in order to reduce storage and infrastructure costs.

The Challenges

  • Lack of standardisation: inconsistent naming convention across the bank
  • Multiple stakeholders: the bank had more than 40 trading applications, each at a different level of maturity and each with their own data repositories. As a result, it was a difficult to ensure that all stakeholders were on-boarded
  • Multiple identifiers: individual clients had multiple identifiers within the bank, which complicated the process of data consolidation
  • Lack of key data definition: a decision needed to be made as to how many data attributes the bank should standardise – 60 or 10
  • Data governance: there was no data governance model to manage the data once it was standardised
  • Engagement: the aims of the project needed to be communicated to all relevant parties to ensure it was not just an IT vision
  • Expensive storage costs: the same data was being stored by multiple applications at significant cost
  • Prioritisation of work: currently driven by the business rather than technology

The Brickendon Solution

  • Work with the business to change the business process flows to incorporate the data changes
  • Prioritise work driven by the business rather than technology
  • Define the key data areas which need to standardised and focus on the 80 per cent-or-so of areas where each application overlaps
  • Initiate the use of a universal container for each area, which can store all the attributes needed for that particular client
  • Define the appropriate and relevant data within each asset class and insert it into each container
  • Ensure that all attribute requirements are fixed at source so that mapping or conversion layers are not created within the organisation
  • Work with each asset class to ensure each application turns off its feed from its own data asset class data store and starts using the client information from the client universal container

Client Benefits

  • Simplification of complex architecture
  • Reduction in headcount
  • Simplification of data management processes
  • Easier access to more useful and consistent data sources and down-stream information across the bank
  • Good data governance thanks to centralised data management in one location
  • Up-to-date business process flows
  • Regulatory compliance and improved risk management

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